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a N = 9 for controls Our results suggest estimated tissue YM can be used to non-invasively distinguish renal tissue affected by CKD from normal renal tissue, even when kidney size does not differentiate the two conditions.
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Therefore, we suggest estimating the probability using the (A_mathrm{L}) approximation in cases with large n.
We suggest estimating them by using the available data as follows [11].
They suggest estimating the performance of random guessing using a Monte Carlo scheme which unfortunately excludes some correct guesses.
The authors suggest estimating the average Platt score (p) and then calculating the p_full.
Peiffer and et al. suggest estimating this quantity from the signal of a normal population (e.g. HapMap samples [ 5]).
This approach suggests estimating the boundaries for conservative and innovative selection using the pathway/process level.
Liao et al. (2006) also suggested estimating daily variograms without accounting for day-today relationships and variations in data availability.
We see that CGBS estimates are stably closer to the suggested estimate regardless of the level of missingness.
We suggest to estimate the average contribution of first.
Independent estimates suggest the figure is closer to 40,000.
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CEO of Professional Science Editing for Scientists @ prosciediting.com